Contents

Abstract

Cash transfer (CT) programmes have become an increasingly important tool
for social protection in low and middle income countries. To date very
little has been done to rigorously examine the economic impacts such
programs may have on beneficiary households and individuals. The regular
and predictable provision of cash may help households overcome various
constraints associated with missing or poorly functioning markets for
goods, inputs, labour, and financial services, and promote greater
productivity and income. The From Protection to Production (PtoP)
project is currently carrying out rigorous quantitative impact
evaluations of cash transfers programs in sub-Saharan Africa (SSA) to
shed light on this hypothesis.

The seven cash transfer programmes included in the project have
different programme characteristics and, more importantly, different
evaluation designs. A toolset of techniques is thus required to handle
these different dimensions and produce comparable and accurate impact
estimates.

The goal of quantitative impact evaluation is to attribute an observed
impact to the programme intervention. A counterfactual is needed to tell
us what would have happened to the beneficiaries if they had not
received the intervention. The most direct way of ensuring a good
counterfactual is via an experimental design (randomised control trial,
RCT), in which households are randomly allocated between a control group
and a treatment group. The randomisation guarantees that on average
control and treatment households will be identical, except for exposure
to the cash transfer programme.

RCTs are often difficult to implement for political, ethical, and
budgetary reasons. When they are not available non-experimental design
techniques are required. Typically these involve propensity score
methods, which construct a statistical counterfactual by matching up
treatment households with similar looking control households in some
way.

Specific analytical questions and corresponding data requirements are
discussed in the paper. One important consideration is the need to
understand how cash transfers affect different types of individuals and
households. This entails examining how impacts vary by household size
(for fixed transfers), how individual labour allocation decisions vary
across gender and age, and how production decisions vary according to a
household’s labour endowment, geographic location and access to key
assets such as land.